Discovering motifs in real-world social networks

Lotte B. Romijn; Breanndán Ó Nualláin; Leen Torenvliet

doi:10.1007/978-3-662-46078-8_38

Discovering motifs in real-world social networks

Lotte B. Romijn, Breanndán Ó Nualláin, Leen Torenvliet

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

4 Citations (Scopus)

Abstract

We built a framework for analyzing the contents of large social networks, based on the approximate counting technique developed by Gonen and Shavitt. Our toolbox was used on data from a large forum—boards.ie—the most prominent community website in Ireland. For the purpose of this experiment, we were granted access to 10 years of forum data. This is the first time the approximate counting technique is tested on real-world, social network data.

Original language	English
Title of host publication	SOFSEM 2015: Theory and Practice of Computer Science
Editors	G.F. Italiano, T. Margaria-Steffen, J. Pokorný, J.J. Quisquater, R. Wattenhofer
Place of Publication	Berlin
Publisher	Springer
Pages	463-474
Number of pages	12
ISBN (Electronic)	978-3-662-46078-8
ISBN (Print)	978-3-662-46077-1
DOIs	https://doi.org/10.1007/978-3-662-46078-8_38
Publication status	Published - 24 Jan 2015
Externally published	Yes
Event	41st International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM 2015) - Pec pod Snezkou, Czech Republic Duration: 24 Jan 2015 → 29 Jan 2015 Conference number: 41

Publication series

Name	Lecture Notes in Computer Science
Publisher	SpringerLink
Volume	8939

Conference

Conference	41st International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM 2015)
Abbreviated title	SOFSEM 2015
Country/Territory	Czech Republic
City	Pec pod Snezkou
Period	24/01/15 → 29/01/15

Keywords

approximate counting
software development
social networks
big data

Access to Document

10.1007/978-3-662-46078-8_38

Cite this

Romijn, L. B., Ó Nualláin, B., & Torenvliet, L. (2015). Discovering motifs in real-world social networks. In G. F. Italiano, T. Margaria-Steffen, J. Pokorný, J. J. Quisquater, & R. Wattenhofer (Eds.), SOFSEM 2015: Theory and Practice of Computer Science (pp. 463-474). (Lecture Notes in Computer Science; Vol. 8939). Springer. https://doi.org/10.1007/978-3-662-46078-8_38

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title = "Discovering motifs in real-world social networks",

abstract = "We built a framework for analyzing the contents of large social networks, based on the approximate counting technique developed by Gonen and Shavitt. Our toolbox was used on data from a large forum—boards.ie—the most prominent community website in Ireland. For the purpose of this experiment, we were granted access to 10 years of forum data. This is the first time the approximate counting technique is tested on real-world, social network data.",

keywords = "approximate counting, software development, social networks, big data",

author = "Romijn, {Lotte B.} and {{\'O} Nuall{\'a}in}, Breannd{\'a}n and Leen Torenvliet",

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doi = "10.1007/978-3-662-46078-8_38",

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editor = "G.F. Italiano and T. Margaria-Steffen and J. Pokorn{\'y} and J.J. Quisquater and R. Wattenhofer",

booktitle = "SOFSEM 2015: Theory and Practice of Computer Science",

address = "Germany",

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Romijn, LB, Ó Nualláin, B & Torenvliet, L 2015, Discovering motifs in real-world social networks. in GF Italiano, T Margaria-Steffen, J Pokorný, JJ Quisquater & R Wattenhofer (eds), SOFSEM 2015: Theory and Practice of Computer Science . Lecture Notes in Computer Science, vol. 8939, Springer, Berlin, pp. 463-474, 41st International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM 2015), Pec pod Snezkou, Czech Republic, 24/01/15. https://doi.org/10.1007/978-3-662-46078-8_38

Discovering motifs in real-world social networks. / Romijn, Lotte B.; Ó Nualláin, Breanndán; Torenvliet, Leen.
SOFSEM 2015: Theory and Practice of Computer Science . ed. / G.F. Italiano; T. Margaria-Steffen; J. Pokorný; J.J. Quisquater; R. Wattenhofer. Berlin: Springer, 2015. p. 463-474 (Lecture Notes in Computer Science; Vol. 8939).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Discovering motifs in real-world social networks

Abstract

Publication series

Conference

Keywords

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